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Large and moderate deviation principles for recursive kernel estimators of a regression function for spatial data defined by stochastic approximation method

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  • Bouzebda, Salim
  • Slaoui, Yousri

Abstract

In the present paper, we are mainly concerned with a family of kernel type estimators based upon spatial data. More precisely, we establish large and moderate deviations principles for the recursive kernel estimators of a regression function for spatial data defined by the stochastic approximation algorithm.

Suggested Citation

  • Bouzebda, Salim & Slaoui, Yousri, 2019. "Large and moderate deviation principles for recursive kernel estimators of a regression function for spatial data defined by stochastic approximation method," Statistics & Probability Letters, Elsevier, vol. 151(C), pages 17-28.
    • Handle: RePEc:eee:stapro:v:151:y:2019:i:c:p:17-28
    DOI: 10.1016/j.spl.2019.03.007
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    References listed on IDEAS

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